Correlation of PDSI monthly averages for the Agencies

Correlation between Chuska monthly average swe and the monthly average PDSI of the agencies

## Warning: Removed 95 rows containing missing values (position_stack).

## Warning: Removed 95 rows containing missing values (position_stack).

## 
##  Pearson's product-moment correlation
## 
## data:  chuska_fd$anomaly_perc and chuska_fd$anomaly_pdsi
## t = 1.9047, df = 94, p-value = 0.05988
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
##  -0.008029559  0.378620112
## sample estimates:
##       cor 
## 0.1927667

PDSI Whole Navajo Nation

## 
## Call:
## lm(formula = nn_mnth_pdsi$pdsi ~ nn_mnth_pdsi$date)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -3.8867 -1.2088 -0.0772  1.2816  5.0680 
## 
## Coefficients:
##                     Estimate Std. Error t value Pr(>|t|)    
## (Intercept)        1.414e+00  2.046e-01   6.908 1.55e-11 ***
## nn_mnth_pdsi$date -1.455e-04  1.779e-05  -8.179 2.55e-15 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.67 on 483 degrees of freedom
## Multiple R-squared:  0.1216, Adjusted R-squared:  0.1198 
## F-statistic: 66.89 on 1 and 483 DF,  p-value: 2.552e-15

Compare PDSI whole NN to total swe for all high elevation regions

## Scale for 'x' is already present. Adding another scale for 'x', which
## will replace the existing scale.

## Scale for 'x' is already present. Adding another scale for 'x', which
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Now let’s looks at correlations between different months

Notation:

  • Winter SWE: November - February (w)
  • Spring SWE: March - April (sp)
  • Early summer PDSI: May - June (esu)
  • Mid summer PDSI: June - July (msu)
  • Late summer PDSI: July - August (lsu)

Compare SWE of Chuska to PDSI watersheds

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## cols(
##   date = col_date(format = ""),
##   waterYear = col_integer(),
##   swe_mm = col_double()
## )
## Parsed with column specification:
## cols(
##   date = col_date(format = ""),
##   pdsi = col_double()
## )
## Parsed with column specification:
## cols(
##   date = col_date(format = ""),
##   pdsi = col_double()
## )
## Parsed with column specification:
## cols(
##   date = col_date(format = ""),
##   pdsi = col_double()
## )
## Parsed with column specification:
## cols(
##   date = col_date(format = ""),
##   pdsi = col_double()
## )

Watershed PDSI timeseries (1981-present)

Chuska SWE Anomalies vs watershed PDSI

Compare Chuska SWE different months of SWE to different months of PDSI

Winter SWE Chuskas and AMJ PDSI watersheds

Mid San Juan and Chuska have the highest correlation of winter swe and AMJ PDSI. Let’s check by year

Compare SWE of Chuska to PDSI chapters of interest

## 
## Call:
## lm(formula = tsaile_pdsi_mnth$pdsi ~ tsaile_pdsi_mnth$date)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -4.1174 -1.3595  0.0247  1.4272  4.6402 
## 
## Coefficients:
##                         Estimate Std. Error t value Pr(>|t|)    
## (Intercept)            1.588e+00  2.181e-01   7.282 1.34e-12 ***
## tsaile_pdsi_mnth$date -1.714e-04  1.894e-05  -9.053  < 2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.783 on 484 degrees of freedom
##   (1 observation deleted due to missingness)
## Multiple R-squared:  0.1448, Adjusted R-squared:  0.143 
## F-statistic: 81.95 on 1 and 484 DF,  p-value: < 2.2e-16

Chuska SWE Anomalies vs Tsaile chapter PDSI

Chuska Average SWE cold season vs PDSI of AMJ of Tsaile